opengeohub / spatial-sampling-ml Goto Github PK

Yes, example is at: https://opengeohub.github.io/spatial-prediction-eml/spatial-interpolation-using-ensemble-ml.html#spatial-prediction-of-soil-types-factor-variable
It works the same way - you just have to prepare the spatial grid for spatial blocking or use the landmap::train.spLearner function.

Originally posted by @thengl in #1 (comment)

How do I add spatial block IDs (blocking = as.factor(rmPF$gid))) to the train.spLearner function for classification (tsk <- mlr::makeClassifTask)?

The current tutorial has longer code to plot maps, add title and customize plots. It would be nicer to use a wrapper function with plotting specifications e.g.:

plot.map <- function(x, y, mtext, ...){
}

where x is the grid, y are the points. For plotting comparison e.g. 2 maps next to each other we would need e.g.:

compare.map <- function(x.left, y.left, x.right, y.right, mtext, ...){
}

@abdelkrim-bsr can you please add this function and systematically adjust in the text?

Do you have an example of resampling using ensemble ml (section 2.4) with classification (instead of regression)?